Interference cancellation system

ABSTRACT

An adaptive interference cancellation system is described. In one example the system operates by receiving a data signal using a DSL (Digital Subscriber Line) and receiving a reference signal, the reference signal corresponding, in part, to noise on the data signal. The reference signal is classified and a noise cancellation signal is applied to the data signal based on the classification.

BACKGROUND OF THE INVENTION

1. Field

The present invention relates to the field of DSL (Digital SubscriberLine) communications receivers, and in particular to filtering noise outof DSL data signals using a reference signal.

2. Related Art

Digital subscriber line (DSL) technologies provide potentially largebandwidth for digital communication over existing telephone subscriberlines (referred to as loops and/or the copper plant). Telephonesubscriber lines can provide this bandwidth despite their originaldesign for only voice-band analog communication. In particular,asymmetric DSL (ADSL) and very-high-speed DSL (VDSL) can adapt to thecharacteristics of the subscriber line by using a discrete multitone(DMT) line code that assigns a number of bits to each tone (orsub-carrier), which can be adjusted to channel conditions determinedduring initialization and subsequent on-line training known as“bit-swapping” of the modems (typically transceivers that function asboth transmitters and receivers) at each end of the subscriber line.

ADSL service uses frequencies in the range of 138 KHz to 1.1 MHz foroperation. Nearly 5,000 AM (Amplitude Modulation) radio stations in theUnited States use frequencies in the range of 540 KHz to 1.7 MHz. Theseradio signals permeate many areas, including areas in which users haveDSL modems in operation. The sizable overlap in frequencies usage cancreate problems for DSL users. In addition, other sources of radiofrequency (RF) interference can contribute to a deterioration in DSLsystem performance as a result of the interference they cause. Finally,other types of interference also can interfere with data signals sent onDSL and other communication systems, such as crosstalk, impulse noise,power-line noise, and other man-made electronic radiation.

RF interference does not distort the entire spectrum identified above.Instead, many sources, such as AM radio stations, affect only a verynarrow portion of the frequency spectrum. ADSL uses 128 or 256 carriers,each of which is a discrete segment of the frequency spectrum about4.3125 kHz wide. Because the ADSL system blocks the transmissions intopackets or symbols of information that are 250 microseconds in length,there is a windowing effect that causes the receiver to see RFinterference within tens to hundreds of kilohertz of the center of eachand every carrier used in the ADSL system. Theoretically, 5 KHz wide RFAM radio interference would tend to affect only 2-3 ADSL carriers, butthe windowing effect leads to each AM radio station possibly affectinganywhere from several to tens of carriers. Impulse, power-line and othernoise sources can often affect a wide range of frequencies.

In many prior systems, the modem affected by RF interference and othernoise sources at a given carrier merely stops using the affectedcarriers or at least reduces the number of bits that the modem carriesin the vicinity of the RF interference, which lowers the performance ofthe DSL system. The effect is especially pronounced when theinterference is present at the end of a long DSL line. Signals that havebeen attenuated significantly during transmission can be completelyovercome by RF interference at a customer's premises. While twisting ofthe transmission loop wires mitigates some of the ingress of RFinterference, it nevertheless represents a significant problem. As thefrequency band used by the DSL system increases (for example, ADSL2+,VDSL), the twisting or balance of the twisted pair becomes lesseffective so that the higher the frequency of the RF ingress, the largerits coupling into the pairs. Furthermore, higher frequencies on atwisted pair tend to be the most attenuated, and so are more susceptibleto distortion by crosstalk at higher frequencies.

In particular, noise and interference often couples most strongly totelephone lines between customers' premises and pedestals (serviceterminals) and the like. Pedestals offer a cross-connection pointbetween lines going from a central office (CO) (or remote terminalcentral office) to a specific customer premises or a few customerpremises (often referred to as a “drop”). The remainder of lines fromthe CO may continue to other pedestals. Typically, there are 2-6 linesin the “drop” segment to each customer, providing extra copper for thecontingency of one or more customers later demanding multiple phoneservices. The relatively exposed DSL transmission loop segment runningbetween the pedestal and customer premises acts as an antenna, pickingup the noise and interference signals, including AM radio broadcasts inthe area. This segment of the line may experience vertical runs of theline that tend to act as higher gain antennas to the RF signals andother noise. Additionally, this last segment is often not well shieldedor employs shields that are not well grounded, leading to additionalgain in receipt of noise and interference by the telephone line(s).

SUMMARY

An adaptive interference cancellation system is described. In oneexample the system operates by receiving a data signal using a DSL(Digital Subscriber Line) and receiving a reference signal, thereference signal corresponding, in part, to noise on the data signal.The reference signal is classified and a noise cancellation signal isapplied to the data signal based on the classification.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will be readily understood by the followingdetailed description in conjunction with the accompanying drawings,wherein like reference numerals designate like structural elements, andin which:

FIG. 1 is a block diagram of an example of a DSL communication systemsuitable for implementing embodiments of the present invention;

FIG. 2 is a block diagram of a CPE receiver with noise cancellationaccording to an embodiment of the present invention;

FIG. 3 is a block diagram of a DSL system between a DSLAM and a CPEaccording to an embodiment of the present invention;

FIG. 4 is a process flow diagram of adaptively cancelling noise from aDSL data signal according to an embodiment of the present invention;

FIG. 5 is a process flow diagram of classifying interference accordingto an embodiment of the present invention;

FIG. 6 is a process flow diagram of selectively updating noisecoefficients according to an embodiment of the present invention;

FIG. 7 is a diagram of a 32 QAM signal constellation suitable for usewith embodiments of the present invention;

FIG. 8 is a diagram of an error between received data and a point withinthe constellation of FIG. 7 that can be measured according to anembodiment of the present invention;

FIG. 9 is a block diagram of an alternative CPE receiver with noisecancellation according to an embodiment of the present invention; and

FIG. 10 is a block diagram of the adaptation and control module of FIG.9 according to an embodiment of the present invention.

DETAILED DESCRIPTION

The following detailed description of the invention will refer to one ormore embodiments of the invention, but is not limited to suchembodiments. Rather, the detailed description is intended only to beillustrative. The detailed description given herein with respect to theFigures is provided for explanatory purposes as the invention extendsbeyond these limited illustrative and exemplary embodiments.

Embodiments of the present invention apply to a modem or othercommunication device that also uses an antenna (or other structurefunctioning like an antenna). The modem receives data signals that aresusceptible to noise from RF and, in some cases, other interferencesources. The noise can affect the modem through unshielded and poorlyshielded portions of any DSL loop to which the modem is coupled. Theinterference sources can include, for example, impulse noise, crosstalkand other man-made electronic radiation. The antenna collects datarelating to the RF and other interference present in the environment inwhich the modem operates.

In addition, crosstalk interference may affect signals on active DSLlines. Crosstalk is a well-known phenomenon in which unwantedinterference and/or signal noise passes between adjacent lines thatoccurs due to coupling between wire pairs when wire pairs in the same ora nearby bundle are used for separate signal transmission. Embodimentsof the present invention can be used to remove one or more significantcrosstalkers in a given system, thus improving the transmission of datato a user, even though all crosstalk might not be removed.

In some embodiments, an antenna, per se, is used. In other embodiments,one or more wires available for other functions also serve as one ormore antennas. For example, when multiple telephone wires are used aspart of the drop from a pedestal or other link to a customer premises,wires in unused and/or inactive DSL lines can be used instead as one ormore antennas. In some modems, the inactive lines may nevertheless becoupled to the modem as they would be if they were active. The phrases“coupled to” and “connected to” and the like are used herein to describea connection between two elements and/or components and are intended tomean coupled either directly together, or indirectly, for example viaone or more intervening elements or via a wireless connection, whereappropriate.

An antenna used in connection with the present invention collectsinterference data relating to its environment (for example, RFinterference from AM radio signals, crosstalk induced by nearby lines,etc.) and provides that data to an interference canceller or filter thatuses the interference data to remove interference noise from DSL orother communication signals. When two types of signals (for example,user payload data and noise) are present on a given line, a second linecontaining one type of signal (for example, the noise alone) allows theremoval of that signal from the mixed signal.

Where user payload data and interference data are present in a given DSLline, the ability to collect the interference data using embodiments ofthe present invention allows the accurate and relatively completeremoval of the interference data, yielding a much more accuraterepresentation of the user payload data. The removal of the interferencedata may occur in a receiver, after receipt of the mixed data signal.

The present invention can be used in a variety of locations to removevarious types of environmental interference sources. Some embodiments ofthe present invention, particularly useful in connection with customerpremises and RF interference, especially AM radio interference, arepresented herein as examples but are not intended to be limiting in anyway. Moreover, while embodiments of the present invention are explainedin connection with one ore more types of DSL systems, othercommunication systems may benefit from the present invention as well andare intended to be covered by the present invention.

The term subscriber loop or “loop” refers to the loop that is formed bythe line that connects each subscriber or user to the central office(CO) of a telephone operator (or possibly a remote terminal (RT) of suchan operator). A typical topology 100 of a DSL plant is presented inFIG. 1. As can be seen, a CO 105 provides high bandwidth transmissionvia a feeder 110 (which can be a high-bandwidth link, such as fiberoptic cable, or a binder with a number of copper lines running throughit). The feeder 110 may connect the CO 105 to a serving area interface(SAI) 120 (which may, for example, be an optical networking unit orONU). From interface 120, a number of copper lines 125 may then extendto a pedestal 130 near one or more customer premises equipment (CPE)locations 140. Such pedestals are common on each block of a street orneighborhood, for example. In some cases, pedestals are intermediatepoints between a CO, SAI and/or other pedestals. For example, in FIG. 1,an inter-pedestal link 128 continues lines that do not divert to theline(s) 135 of a customer 140 on to another pedestal and thussubsequently to one or more other CPEs.

Pedestals offer a cross-connection point between lines going to one ormore customer premises (often referred to as a “drop”) and the remaininglines that may continue to other pedestals. Typically, there are 2-6lines in the “drop” segment to each customer, providing extra copper forthe contingency of one or more customers later demanding multiple phoneservices. The cable back to the ONU or central office usually does nothave 2-6 times as many phone lines as would be needed by all thecustomers (because not all customers would have demanded that manyphones). However, the pedestal drops typically have extra copper. Acustomer's modem can be connected to extra lines for a number of reasons(for example, future bonding and/or vectoring of lines and/or signals,cancellers such as those covered by embodiments of the presentinvention, selection of a best line by the modem if the lines actuallyare connected all the way back, etc.) This extra copper may be exploitedin some embodiments of the present invention when extra wires and/orlines are used as the antenna(s) for the modem.

A basic modem is shown in FIG. 2, incorporating one or more embodimentsof the present invention. In the example of FIG. 2, the removal of RFinterference is used as an exemplary interference cancellation performedin the time domain, rather than the frequency domain. This facilitatescancellation of the RF interference noise because the RF interference isasynchronous. However, removal can be performed in the frequency domainin some cases, for example by treating successive DFT output blocksymbols in a receiver, and the invention includes RF interferencecancellation in all such circumstances. The type of interference beingremoved may dictate or otherwise make various options more preferablethan others.

FIG. 2 illustrates a remote modem, transceiver or other communicationdevice 300 operating in its receiver mode. Communication device 300 ofFIG. 2 receives transmitted data 390 using an active DSL line 392. Theline 392 typically includes at least one segment that is unshielded (orpoorly shielded) and thus often highly receptive to RF and other typesof interference (depending on various factors, such as the sufficiencyof twisting of the wires in line 392). Thus the transmitted data 390received by the modem 300 may very well include payload data and RF orother interference noise. The analog signal on line 392 is converted todigital data at converter 322.

Antenna means 394 may be an antenna, per se (such as an AM radio compactantenna or the like), one or more wires in a second or additionaltelephone/DSL line, or any other suitable device or structure configuredto collect interference data relating to at least one type ofinterference noise affecting signals being received by the modem 300.The interference data collected by the antenna means 394 are provided tointerference canceling means 320 in the modem 300. Particular structuresfor the interference canceling means 320 are disclosed herein, butothers may be used instead, depending on the type of interference databeing collected, the type of communication signals being received by themodem 300, the processing needed to use the interference data to removesome or all of the interference noise affecting signals received by themodem 300, etc.

In the example system of FIG. 2, the analog interference data receivedby antenna means 394 is converted from analog to digital form by aconverter 322. All of the processing described as occurring in digitalsignals may also be done with analog signals from line 392 and antenna394. Analog-to-digital-converter (ADC) 322 can be differentially coupledto a second line or can use a common reference such as one wire from theactive line and couple to either of the wires of a second telephone lineif the antenna is a wire from a second telephone line. The digitalsignal from antenna 394 is then filtered using an adaptive filter 324 inmodem 300. The data signal from the output of ADC 322 may be controlledby a delay block 323 (so that the old RF interference is already in theadaptive canceller and thus renders downstream cancellation causal).

The appropriately conditioned RF interference data and transmitted datasignals are then input to a subtractor 325, which can perform a simplesubtraction to remove the RF interference noise from the transmitteddata. Subtractor 325 can perform selective subtraction in someembodiments of the present invention. That is, subtraction may beperformed under specified conditions. For example, if the interferencenoise level (determined, for example, by measurement, estimation, etc.)is not above a given subtraction threshold, then the noise cancellationsignal, values, etc. can be zeroed so that no noise cancellation isattempted. This can be used where the interference noise and/orinterference data is not reliable (for example, old, etc.) or has beendetermined to be far enough away from a desired level to makecancellation attempts imprudent and/or undesirable.

The output of subtractor 325 is used to assist the filter 324 inadapting the signal from antenna 394. Embodiments of the presentinvention might use a digital tapped-delay-line filter whosecoefficients are adapted by well-known adaptive algorithms such as theLMS algorithm (perhaps with leakage to allow for the narrow-band inputand possible instability).

The coefficients used by the filter can be adaptive and can be updatedfrom time to time, constantly, and/or adapted in other ways. Accordingto one embodiment of the present invention, the coefficients can beupdated selectively. For example, when the interference data (that is,the interference noise that is measured, estimated, etc.) indicate thatthe interference noise does not meet and/or exceed an updatingthreshold, then updating can be turned off, not performed, etc. Statedanother way, the adaptive filtering can be “selectively adaptive” basedon an updating threshold level or value for the interference noise.

Embodiments of the present invention use the RF interference datacollected by the antenna 394 to remove noise in the transmitted data 390that is caused by RF interference in the frequency range used totransmit data downstream to modem 300. In the case of the most commonforms of ADSL, for example, this would include RF interference in therange of 138 kHz to 1104 MHz. This naturally would include AM radiointerference found in the band of 540 KHz to 1.1 MHz. Some forms of ADSLmove the downstream start frequency, which typically is 138 kHz, as lowas 0 Hz and as high as 200-300 kHz. Some forms of ADSL, most notablyADSL2+, move the downstream end frequency as high as 2.208 MHz whileVDSL moves this frequency to 8.832 MHz, 17.668 MHz or even as high as 30MHz. These extended bands could include AM radio interference found inthe band of 540 kHz to 1.6 MHz as well as amateur radio bands at 1.8-2.0MHz, 3.5-4 MHz, 7.0-7.1 MHz and several others at higher frequencies.

Other sources of RF interference might be present, including but notlimited to radio beacons used for navigational purposes, long-waveradios, power-line communications used for broadband access (BroadbandPower-Line, BPL) and a variety of other sources. Moreover, noise from asource of another type of noise that is not RF interference noise (forexample, crosstalk from another DSL line) could couple into the activeDSL line and the “antenna” line/wire. Such noise also could beeliminated by the canceller of the present invention, even though thenoise might not be described and/or characterized as an RF signal, perse.

As mentioned above, the interference noise does not have to be RF noiseso long as the same noise source impinges on both the active data lineand the antenna. For example, one such alternative noise could be a DSLsignal on a separate, but nearby, telephone line that couples into boththe active data line and the antenna used in this invention. For optimumresults, the number of antennas should exceed the number of significantnoise sources at any single frequency or tone of a DMT DSL system inorder to completely cancel each significant noise source. In otherwords, the noise can be completely cancelled when all of the noisesources are completely correlated across the data lines and antennalines. Thus, if there is one antenna, one independent noise source canbe cancelled at each frequency. However, not all noise sources need tobe cancelled for substantial performance benefits to be realized.

In addition, a smaller number of antennas may still be able to reducemany significant sources of noise. To retrieve the data, it is notalways necessary to completely cancel a noise source, only to reduce itenough that the signal can be retrieved. When the number of antennas isless than the number of (significant) noise sources, the noise cancellercan still be used with good performance. For example, for afrequency-domain noise canceller, if there exists a dominant noisesource for all the tones, even if it affects different tonesdifferently, most of the noise can still be cancelled.

Once the RF interference noise has been removed, the data is sent to adiscrete Fourier transform module 326, constellation decoder 328 andtone reordering module 330. Data bound for the interleaved path 342 of aDSL modem is then sent to a deinterleaver 332, descrambler and FECdecoder 336 and interleaved cyclic redundancy code prefix (crc_(i))detector 338. Similarly, data bound for the fast path 344 of modem 300is sent to descrambler and FEC decoder 334 and fast cyclic redundancycode prefix (crc_(f)) detector 340. Finally, the data is deframed inmodule 346 and provided to a user as payload data 396.

In another embodiment of the present invention, the modem is connectedto multiple telephone/DSL lines, as shown, for example, in FIG. 3, inwhich a modem 400 is connected to pedestal 404 by a multiple loopsegment 406 comprised of 8 wires 411 through 418, which are the 8 wiresof 4 loops 421, 422, 423, 424.

In the example of FIG. 3, only loop 424 (using wires 417, 418) isactive, loops 421, 422, 423 being inactive. Thus wires 411 through 416are not in use for DSL communication purposes. Instead, at least one ofthese wires, wire 416, is used as an interference data antenna for modem400. In this case, wire 416 is practically identical to wires 417, 418of active loop 424 (for example, being approximately the same length andhaving the same orientation, possibly being the same material/type ofwire, and possibly having the same amount or absence of shielding). Thismeans that wire 416 will receive practically identical RF and/or otherinterference signals as those received by loop 424. If more than onesource of RF and/or other interference (for example, crosstalk from oneor more additional DSL lines) is present, additional inactive loops'wires can be used similarly, if desired.

The interference data collected by wire/antenna 416 and the incomingdata from active DSL loop 424 is converted from analog to digital formby converters 442. Again, the interference noise data is filtered byfilter 441, which bases its conditioning of the interference noise onthe output of subtractor 440. Filter 441 can be selectively updated asexplained for filter 324 in FIG. 2. The received data from loop 424 canbe delayed by delay element 443. The conditioned data from loop 424 andantenna 416 is then input to subtractor 440 so that the interferencenoise can be removed and the remaining user data passed on to the othermodem components, modules and/or processing. The subtractor 440 canperform a selective subtraction as explained for module 325 in FIG. 2.Additional antennas can be brought into service using other wires frominactive loops of segment 406. For example, as shown by the dashedconnections 454, wires 413, 414, 415 can be employed as needed. The ADC442 may then be more than just a single converter and may instead be anysuitable conversion circuitry. Similarly, in such a case, filter 441 maybe adaptive filtering circuitry.

Finally, multiple wires in segment 406 can be used to removeinterference. The systems disclosed in U.S. Ser. No. 10/808,771, filedMar. 25, 2004, entitled “High Speed Multiple Loop DSL System,” canprovide extra phone lines and/or antennas and cancel interference inmore than one telephone line (if they are bonded and vectored asdescribed in the referenced '771 application). Thus, the system can beviewed as having additional lines/antennas, and again the RF or othernoise and/or interference is canceled in all the lines.

In the example of FIG. 3, there are 8 wires in the segment 406, only twoof which are in use, the two used for loop 424. The other 6 wires couldbe used as follows wire 416 for collecting RF interference data, wires411-415 for collecting interference data for the 5 most significantcrosstalkers affecting loop 424. That is, in a system having N telephoneloops or lines available, where one of the telephone loops is the activeDSL line, one or more wires in the remaining N−1 loops can act as theantenna or antenna means to collect interference data. Since there are 2wires in each loop, there are 2(N−1) wires available for collectinginterference data affecting the signals received by a modem using theactive DSL line. Any suitable interference canceling means can be usedin connection with the antenna(s), including more than one type ofinterference canceling structure where more than one type ofinterference noise is being removed and/or canceled. Each wire can beused to remove a single source of interference noise (for example, AMradio interference, a household appliance near the segment, crosstalk,etc.). Each wire's interference data can be converted to digital formand be filtered appropriately.

A method for removing noise from DSL or other communication signalsreceived by a modem or other communication device, according to oneembodiment of the present invention, is shown generally in FIG. 4.Method 700 starts with the collection of interference data at 710 beingperformed by one or more suitable antennas, depending on the type(s) ofinterference present and the available antenna structure(s). Theinterference may be RF interference such as AM radio signalinterference, crosstalk from neighboring communication lines, or otherinterference. The interference may be collected by an AM radio antenna,an inactive DSL loop wire, and active DSL loop wire or an antennaspecifically provided for collecting this type of interference. At 720the communication signal, including the user's payload data andinterference noise, is received by the communication device. In thepresent example, this is a DSL data signal which may be in a variety ofdifferent forms, including a discrete multitone (DMT) data signal.

At 730, some or all of the interference noise is subtracted from thereceived communication signal using the interference data supplied bythe antenna(s). When multiple wires and/or antennas are available andmore than one source of interference noise is present, method 700 may beapplied iteratively or otherwise to remove more than one type and/orsource of interference, either completely or partially, according to oneore more embodiments of the present invention. In some embodiments ofthe invention, the subtraction is applied only if the measured noise isover a threshold. The thresholding determination may be applied in avariety of different ways as described in more detail below.

Finally, at 740, the filtering coefficients or any other parameters ofthe filtering are updated. The updating can be done by monitoring thenoise received and the effectiveness of the filtering. The coefficientsthat determine the amount and the nature of the filtering may then beiteratively updated to improve performance. As indicated, the selectiveupdating of the filtering coefficients at 740 returns the method 700 tostep 710. The method 700 can be operated continuously so that theprocess repeats and additional interference data is collected again at710 for the next communication signals to be filtered.

FIG. 5 shows aspects of the noise removal method of FIG. 4 in moredetail. The method 800 of FIG. 5 begins with obtaining reference samples810, similar to collecting interference data 710 in FIG. 4. In oneembodiment, the reference samples correspond to samples of the signalthat is carried on the adjacent twisted pair, an antenna or any othernoise receiver. As mentioned above, these samples will typicallycorrespond to noise from any of a variety of different sources. In thepresent example, typical noises experienced near the CPE are the typicalnoise sources in homes and office and would include other RF devices,such as radios, computers, telephones, and entertainment equipment, aswell as noises from appliances, such as coffee makers, heaters,dishwashers, hair dryers and may even include larger plant equipmentsuch as water pumps, ventilation systems, air purification and powergenerators, among others. For a system at the other end, near theCentral Office, different noise sources may be present and would includetelephony and data switching equipment and cross-talk between differentlines and systems.

Using these reference samples, at 820 some properties of the referencesamples are measured. Any measure that can provide some uniqueidentification of the noise source or a combination of noise sources maybe used. Statistical measures may be particularly useful if the noisehas irregular fluctuations that tend to average out over time. Powerspectral density can be used to provide a distinctive signature for thenoise source or a combination of noise sources, however, otherproperties can be measured instead or in addition to the power spectraldensity. Frequency signatures and impulse response signatures and othermeasures may be particularly useful. Probability distribution functions,means, medians, variances, moments, peak-to-average-ratios and otherproperties of the estimated samples may also be particularly useful.Such measures can be individually computed for one or more sub-carriers,or for groups of sub-carriers after appropriate processing of thereference samples.

At 830 the estimated properties of the reference samples are compared tothose of known types of noise. This allows the noise to be identified.This can be done in any of a variety of ways. In one embodiment, theproperties are expressed numerically and applied to a look-up table. Theproperties are the input side of the table and coefficients are on theoutput side. If there is a match at 840, then at 860, coefficients orparameters for the identified type of interference are provided for usein the subtraction at 730. 730 refers to the interference and noisesubtraction as being selective. In one embodiment, this selection meansthat subtraction is applied only if the measured noise is over athreshold. In other words if the noise is low, then there will be nonoise cancellation applied to the data signal. In another embodiment,this selection is provided by method 800 using the matching at 840. Thematching allows appropriate subtraction coefficients or parameters to beselected for application to the noise. This selection can be used toimprove the quality of the filtered data signal. The thresholding andthe matching can both be performed in a single system. In oneembodiment, a low noise signal will match with a low noiseclassification that produces a zero valued subtraction coefficient.

If there is no match, then at 850, a new type of interference iscreated. Subtraction coefficients for this new type of interference arethen provided at 860 for use in the filtering or subtraction. The newcoefficients can be set at some initial generic value or selected basedon the estimated properties. In one embodiment, the new coefficients arezero. FIG. 5 provides a method for classifying the interference andnoise in the obtained or collected reference samples. The classificationis then used to select at 840 an appropriate measure with which tocounter the interference and noise. As a result, the subtractionoperation at 730 is able to adapt to changing circumstances.

Consider, for example, that a washing machine has just entered a spincycle and the motor that drives the spinning chamber is poorly shielded.In the spin cycle, the motor moves at its highest power and speedsetting which causes it to generate its highest amount of RFinterference. This interference is different from that produced duringthe wash cycle and is similar to AM radio emission, but includes otherforms. If this type of interference is already known, it will beidentified at 840 and an appropriate counter will be selected. When thespin cycle ends in 5 or 10 minutes, the method 800 will find that theproperties of the noise has changed at 820 and at 860 will classify thenoise differently.

FIG. 6 shows a method 900 that can be performed independently of themethod of FIG. 5 to improve on the selected subtraction coefficientsduring the course of operation of the filter. At 910, a decoder error isobtained. This decoder error is used as a representation of how well thesystem is able to decode the received data. If the decoder error is low,then the coefficients are effectively subtracting a significant amountof the noise and interference. If the decoder error is low, thensignificant improvements can be made. The particular nature of thedecoder is described in more detail below. At 920, the error ratemeasured by a FEC (Forward Error Correction) system is evaluated todetermine if it is too high. If the error rate is too high, then at 930no update is performed and the method 900 returns to look at the decodererror. An excessive FEC error rate in this embodiment of the inventionis used to determine whether, the received data has high enough qualityto allow the coefficients to be improved. In one embodiment, thethreshold to decide whether the error rate measured by the FEC system isexcessive may be variable to allow the interference cancellercoefficients to initially converge. The threshold can be fixed to alower value after the interference canceller coefficients haveconverged.

The quality measure performed at 920 uses an FEC (Forward ErrorCorrection) rate. Any other measure of the quality of the receivedsignal may be used instead. In the present example, the FEC rate ischosen because an FEC decoder is used in the receiver and the resultsare readily available for use in this method 900. In another embodiment,the decoder error is used. As explained below, the FEC error is ameasure of the number of errors in the decoded data. As a result, it isa numerical quantity that represents the accuracy of the data after allof the noise filtering. This measure is readily available and convenientwhen the received data includes error correction codes. If there are noerror correction codes or if the result of the error correction is notreadily available to the method 900 then other measures may be used.

The operation at 920 limits the updating of coefficients to when thesystem is receiving data that has noise or interference within somelimited range. This provides for greater accuracy in some techniques forupdating the coefficients. The particular amount of permissible noisecan be adapted to suit the particular updating algorithm.

At 940, the reference sample is obtained. As mentioned above, this is asample of the noise taken from the antenna or another wire pair. At 950,the interference classification determined in the method 800 isobtained. At 960, the subtraction coefficients corresponding to theinterference classification are obtained. These are the coefficientsthat are to be updated. These operations indicate that the coefficientupdating process 900 is designed in this example to operate on thecoefficients that are currently in use. This approach presents anadvantage that the reference samples are current and the classificationoperations have been performed. The method 900 can also be performedusing stored values depending on the particular implementation.

At 970, the coefficients are updated and stored in the memory that isused by the noise and interference subtraction. The storage step allowsthe coefficients to be made immediately available for use. The methodthen returns to 910 to repeat with new values. If, after updating, thenoise classification is the same, then the same coefficients will beupdated again. After several repetitions, the coefficients should reachthe maximum possible accuracy allowed by the system.

Any of a variety of different updating processes may be used to suit aparticular implementation. One example can be understood in the contextof FIGS. 7 and 8. FIG. 7 shows an example 32 point QAM (QuadratureAmplitude Modulation) constellation commonly used for ADSL1, ADSL2,ADSL2+ and VDSL2.The constellation points, are positioned with respectto orthogonal horizontal and vertical axes, where the positions aredenoted by coordinates (X, Y). All of the constellation points lie oncoordinates with odd integer values of ±1, ±3, ±5. In this figure, forsimplicity the constellations points themselves are not labeled. Theincoming data stream is in the form of variations in phase and amplitudemodulation each representing a constellation point. The actual pointsreceived are moved from their precise positions by many influencesincluding the noise and interference discussed above. Each constellationpoint represents a data symbol.

The dashed lines represent the decision boundaries of the constellation.In other words, the decoder will interpret any signal that is within thedashed lines as corresponding to the constellation point within thedashed lines. The constellation point is then applied to a look-up tableto produce the appropriate data symbol. When trellis coding isimplemented, the decoder will apply sophisticated sequence estimationtechniques (e.g. Viterbi decoding) to produce the appropriate datasymbol.

FIG. 8 shows graphically the computation of an error sample for aparticular sub-carrier between the received data sample r andcorresponding ideal constellation point c. In this example, forsimplicity of illustration the received sample r is shown as fallingwithin a decision boundary of a constellation point indicated bycoordinates of (1,1). This can be expressed as c=(+1, +1). Theconstellation point c is the “decision” result of a decoder (e.g. sliceror trellis decoder). If the “decision” is correct, then the decodedconstellation point is the same as the transmitted constellation point.

The complex, or two-dimensional error, e, corresponds to the distancebetween r and c. This is the hypotenuse of the triangle of FIG. 8 thathas one side of length e_(x) and the other side of length e_(y). Thiscan alternatively be defined using complex vector notation as e=r−c,where e is the complex error defined as e=e_(x)+j·e_(y) with an in-phasecomponent e_(x) and a quadrature component e_(y), r is the complexreceived data sample defined as r=r_(x)+j·r_(y) with in-phase componentr_(x) and quadrature component r_(y), and c is the decision symboldefined as c=c_(x)+j·c_(y) with in-phase component c_(x) and quadraturecomponent c_(y). Again, the valid values of c_(x) and c_(y) are eachfrom the set of values ±1, ±3, ±5, etc. The in-phase componentcorresponds to the horizontal axis in FIGS. 7 and 8 and the quadraturecomponent corresponds to the vertical axis.

Returning to the updating operation at 970, the coefficients areadjusted in an effort to reduce the error e shown in FIG. 8. Theupdating of the filter coefficients can be performed using any of avariety of different techniques. Those for adaptive filtering, such asLeast-Mean-Squares (LMS) method and the Recursive-Least-Squares (RLS)method are appropriate examples.

A LMS method can be applied as follows. The inputs are the referencesample, y, the error, e and the starting filter coefficient w. These canbe the values obtained at 940, 910 and 960, respectively. Thereplacement coefficient can then be selected by applying an adaptationthat adjusts the original coefficient by the amount of the error. Suchan operation can be performed in many different ways as, for example, anLMS operation.

The updating process can be expressed more precisely as follows:

-   -   Inputs:

Reference sample, y=y ₁ +j·y _(Q)

Error sample, e=e ₁ +j·e _(Q)

Old filter coefficient, w _(old) =w _(1,old) +j·w _(Q,old)

-   -   Output:

New filter coefficient, w _(new) =w _(1,new) +j·w _(Q,new)

-   -   Operation:    -   Adaptation constant, μ

w _(new) =w _(old) +μ×e*×y

-   -   where * denotes the “complex conjugate”

The methods 800, 900 described above can be implemented in manydifferent ways including software and hardware approaches. One exampleimplementation is shown in FIGS. 9 and 10. FIG. 9 shows a DSL receiver500 with an input stream for data 501 and an input stream for noisesignals 502, that are primarily noise and interference. The input datastream is provided at a terminal shown generally as an analog front end503 that represents a connection for a twisted wire pair or anothersuitable data carrier configuration. The analog data is sampled at ananalog to digital converter (ADC) 505, converted from serial to parallel(S/P) at 507 and converted to the frequency domain by an FFT (FastFourier Transform) 509. The FFT corresponds to the DFT shown in otherfigures. This particular receive chain is particularly suitable forVDSL2 and may be modified to suit other DSL and other communicationsconfigurations.

The noise signal has a parallel receive chain. In this example, thecarrier for the reference samples is another twisted wire pair that hasroughly the same physical path as the pair that carries the data. Thetwo receive chains are designed to be as similar as possible so that thenoise and interference received at the end of the receive chain is assimilar as possible to that of the data receive chain. Accordingly, thereference connection has an analog front end 504 to terminate thetwisted pair. This is coupled to an analog to digital converter 506 tosample the noise and obtain samples of the reference signal. Thereference samples are converted to parallel data at a converter 508 andthen transformed at an FFT 510. If the reference line is also carryingother data, such as analog voice, additional filtering (not shown) maybe provided to remove the other data before the noise and interferenceis sampled. As another alternative, a single receive chain may be usedthat is switched between the two lines.

In the present description, any signal on the reference line is ignored.In one example, the reference line may be unused except as a referenceline as described herein. However, it is not required that the line notbe used. As mentioned above, the line may carry analog voice. An analogfilter can be used to remove the analog voice signals in or before theanalog front end. Alternatively, the reference line can be used fordigital signals and these can be filtered out. In another example, whenthe data line complies with a format that uses multiple tones, such asDMT, the reference line can also be used for DSL data. This can allowthe data rate for the CPE to be increased. In order to provide thereference signal, some of the DMT tones can be reserved for referencepurposes. The analog front end can filter out the other tones, or theA/D can sample only around the reserved tones.

The data and reference sample are provided as inputs to a processingblock 511. For the data, this block subtracts the noise and interferenceat an adder 513 and then this filtered data is applied to a decoder 515.The decoder can take any of a variety of different forms depending uponhow the input data is encoded. In the example described above, thedecoder receives a complex valued phasor that points to a particularconstellation point in, for example, the 32 QAM constellation of FIG. 7.In many DSL systems the size of the constellation will be based on thehighest data rate that the DSL loop can sustain on a given sub-carrier.The constellation may have as few as 2 points and as many as 2¹⁵ points,depending on the quality of the wired connection. The output of thedecoder is then a value for the constellation point that is the closestto the input value. This can be expressed as a corrected phasor, asymbol or a binary data block.

The decoded value is then passed to a forward error correction block517. In systems such as ADSL1, ADSL2, ADSL2+and VDSL2, the input dataincludes Reed Solomon error correction codes. These codes will allow theblock to correct errors in the data using the codes. The number oferrors that can be corrected will depend upon the length of the codesselected for the particular application. The corrected data is thensupplied to the requesting customer equipment, such as a personalcomputer, data terminal, or entertainment center.

The reference samples 521 after transformation to the frequency domain510 are applied as an input to an adaptation and control block 519. Thisblock stores, maintains and updates the subtraction coefficients, w,that are operated upon in methods 800 and 900. The adaptation andcontrol block also provides the coefficients, w, to a multiplier 523.Typically, only one coefficient will be provided to the multiplier atany one time at any one sub-carrier. The provided coefficient will bebased on the noise classification. The multiplier combines the providedcoefficient with the reference samples 523 and the result is sent to theadder as the noise to be subtracted from the input data.

The adaptation and control block 519 in order to maintain thecoefficients receives several different inputs. While the use of theseinputs is described more in

FIG. 10, the sources of the inputs are best seen in FIG. 9. The inputsinclude the reference samples 521. The FEC block provides a value 525that represents the quantity or quality of the errors that it has foundor corrected. This can be as simple as a binary or true/false line thatindicates whether the data can be corrected or not. It may alternativelybe a precise indication of the number and types of errors that have beenencountered and corrected.

The decoder error is provided by comparing the decoder 515 output 527 tothe decoder input 529. In FIG. 9, this is shown as providing the decoderinput and the negative of the output to an adder. The result representsthe decoder error that is an input to the adaptation and control block.The decoder error can also be represented in a simple or complex way. Inthis example, it corresponds to the error, e, shown in FIG. 8. In thedescription of FIG. 8, e, was represented in the form of a vector withlength and direction. The amount and the direction can both be used toupdate the subtraction coefficients, however, good results can beachieved with only one of the amount and direction.

Referring to FIG. 10, the reference samples 521 are provided to aninterference classification module 541 of the adaptation and controlblock 511. The interference classification module determines aclassification for the reference samples. This may be done for exampleusing the method 800 of FIG. 5, described above. The resultingclassification is fed to a selector 545 so that an appropriatesubtraction coefficient is provided to the filter multiplier 523. Theselector 545 has as inputs a set of memory registers 547. The value ineach register corresponds to a coefficient, w, for a particular noiseand interference classification. This structure allows an appropriatestored coefficient, w, to be provided as noise conditions change.

The selector also has a default input 549, indicated as zero in thisexample. This default input can be used for any noise and interferenceconditions that do not match with a classification. It can also be usedfor new coefficients. When the default input is used as the subtractioncoefficient, the noise filter 513 essentially subtracts zero from thedata signal. In addition, the zero coefficient can be used if thestrength of the noise signal is low. If the classification is based onthe strength of the signal, such as it power, amplitude, power spectraldensity or some similar measure, then the signal strength is alreadyderived. Otherwise a separate signal strength measure may be used.

The adaptation and control block 519 also updates the coefficients, w,using, for example, the method 900 shown in FIG. 6. As indicated in FIG.10, the classification is also provided to an update coefficients module521. Based on the current classification the update coefficients modulecan read the corresponding coefficient, w, from the memory 547. Usingthe corresponding reference sample 521 and the decoder error, the updatecoefficient module can update the coefficient value and write theupdated value back into the memory 547. This will cause the selector 545to provide the updated value at the next cycle. The update coefficientmodule will then perform the update method on the updated value. As aresult the coefficient value can not only converge to a very preciseresult, but can also adapt to changing conditions. This can be used togreatly enhance the quality of the samples that are fed to the decoder.

The same update process may also be applied to new coefficients in thememory that start with a default value of zero or any other value. Whilethe starting coefficient value may not be precise or provide optimalresults, through the updates, the coefficient will be improved.

In the illustrated example, the decoder error value from the adder 531is not fed directly to the update coefficient block 551, but is insteadfed to a selector. The alternative value for the selector is a zero. Theselection between the actual decoder error value and zero is made basedon the FEC error value 525. As a result, if the PBC errors are low, thenthe decoder error is provided to the update coefficients block and themethod 900 of FIG. 6 will determine a new coefficient intended to reducethe error. On the other hand, if the FEC errors are high, then the zerowill be selected. The update coefficient module will interpret this asmeaning that there are no decoder errors and will not update thecorresponding coefficient. This is one example implementation for whatis shown as a threshold decision block 920 and return 930 in FIG. 6.This same functionality may be implemented in a variety of other waysdepending on the particular application.

The principles and operation described above may be better understoodthrough the consideration of a specific example. This example assumesthat the DSL transmitter is sending a Discrete Multi-Tone (DMT) signalwith 10 tones to the receiver of FIG. 9. 10 tones has been selected forease of understanding. Typically a DMT system will use from 32 to 4096tones.

Using FIG. 9 as reference, the output of the “top” FFT 509 block will beX_(1, X) ₂, . . . , X₁₀ , where each of the X_(i) is a complex receivedsample of the first line corresponding to tone i. The output of the“bottom” FFT block 510 will be Y₁,Y₂, Y¹⁰, which are also complexreceived samples of the second line.

The interference cancellation operation 513 is performed for each toneindividually, thus:

X _(i,after) =X _(i) −W _(k,i) Y _(i)

X^(i,after) is the result of the interference cancellation operation andalso the input to the decoder 515, corresponding to tone i. W_(k,j) is acomplex filter coefficient, corresponding to tone i and to interferencetype k. The interference type is the result of the interferenceclassification block 541 in FIG. 10.

The output of the decoder 515 can be denoted by D₁, D₂, . . . D₁₀ (oneoutput sample for each tone). This output is used to form a Reed-Solomoncodeword consisting of N bytes. R bytes out of the N bytes are “parity”bytes. The K=N−R remaining bytes are the “payload” bytes. N can varybetween 32 and 255. R can vary between 0 and 16. The Reed-Solomondecoder 517 decodes the codeword with the following possible outcomes:

The originally transmitted codeword is recovered;

-   -   The decoder cannot recover the original codeword and an        indication 525 is produced;    -   The decode mis-decodes and produces an incorrect codeword        without any indication.

By comparing the Reed-Solomon codeword before and after the Reed-Solomondecoder, an indication 525 is produced of whether the Reed-Solomondecoder detected errors. For example, if the payload bytes at the inputof the Reed-Solomon decoder 517 are:

-   -   0A 3B 49 C7 80 A5 68 D9 F7 AA 52 0E 23 1F 91 0E    -   (In this example, two hexadecimal digits correspond to a byte.        K=16 bytes, so there are 32 digits, corresponding to one symbol        from the decoder.)

If the payload bytes at the output of the Reed-Solomon decoder are:

-   -   0A 3B 49 C7 81 AS 68 D9 F7 AA 52 0E 31 1F 91 0E    -   then it is clear that the Reed-Solomon decoder detected errors        and corrected them. These errors are in the fifth byte in which        80 was corrected to 81 and in the thirteenth byte in which 23        was corrected to 31.

Classification

The received reference samples Y₁, Y₂, . . . , Y₁₀ are also used forinterference classification in the classification module 541. For thepurpose of computing statistical quantities, the samples may becollected several times. This allows statistical averages to be computedand avoids the risk that any one particular sample will not be like thesurrounding sample. An example of a statistical quantity is the measuredpower spectral density (PSD). The PSD can be estimated as follows:

${P\; S\; D_{i}} = {\frac{1}{N_{ave}}{\sum{{Y_{i}}^{2}\mspace{14mu} {for}\mspace{14mu} {the}\mspace{14mu} P\; S\; D\mspace{14mu} {of}\mspace{14mu} {tone}\mspace{14mu} {i.}}}}$

In the above expression, the averaging is performed over N_(ave)observations of Y_(i).

A typical approach for classification would be the following:

-   -   Let PSD^(classA) _(i) denote the pre-stored PSD corresponding to        an interference type belonging to “class A”, and for tone i.

If Σ|PSD_(i)−PSD^(classA) _(i)|² ≦c (where c is a known constant), thenthe interference classification block indicates that the interferencetype is “class A”. Of course, this comparison can be extended tomultiple interference types.

If Σ|PSD_(i)|² ≦c′ (where c′ is a known constant), then the interferenceclassification block indicates that the interference is very weak, andthat no interference cancellation should be attempted.

If the comparison against all known interference types and against weakinterference produces no “match”, then a new interference type can becreated as follows:

PSD ^(classNew) _(i) =PSD _(i)

In any actual system, there will be a limited number of registersavailable to store coefficients. If the noise has more variations, thanthere are registers, then old coefficients can be replaced with newcoefficients. In this way, the registers will contain the most recent,and perhaps the most needed coefficients. To determine whichcoefficients to write over, each time a comparison is performed, a countof the successful “matches” against known interference types can bemaintained. When the known interference types reach an upper limit, thenthe interference type with the smallest count can be discarded to allowfor a new interference type to be created. The count can be kept in thesame memory 547 that holds the coefficients or in some other place.

Coefficient Updating

The basic operation for coefficient updating is described above.

The result of interference classification determines which of theW_(k,j), k=classA, . . . coefficients to update.

In the described example, if “excessive errors” are observed, then noupdating is performed. This is similar to forcing e=0 as described forthe selector 553 of FIG. 10. Excessive errors can be detected bycomparing the Reed-Solomon codeword before and after the Reed-Solomondecoder or in a variety of other ways.

Generally, embodiments of the present invention employ various processesinvolving data stored in or transferred through one or more controllers,DSPs (Digital Signal Processor), ASIC (Application Specific, IntegratedCircuit), processors, or computer systems. Embodiments of the presentinvention also relate to a hardware device or other apparatus forperforming these operations. This apparatus may be specially constructedfor the required purposes using hardware or firmware configurations, orit may be a general-purpose computer selectively activated orreconfigured by a computer program and/or data structure stored in thecomputer. The hardware embodiments may also use a combination ofdedicated hardware, firmware, microcode and software.

The processes presented herein are not inherently related to anyparticular circuit, computer or other apparatus. In particular, variousgeneral-purpose machines may be used with programs written in accordancewith the teachings herein, or it may be more convenient to construct amore specialized apparatus to perform any desired method steps. Aparticular structure for a variety of these machines may be adapted tosuit any of a variety of different purposes.

Embodiments of the present invention as described above employ variousprocess steps involving data stored in computer systems. These steps arethose requiring physical manipulation of physical quantities. Usually,though not necessarily, these quantities take the form of electrical ormagnetic signals capable of being stored, transferred, combined,compared and otherwise manipulated. It is sometimes convenient,principally for reasons of common usage, to refer to these signals asbits, bitstreams, data signals, control signals, values, elements,variables, characters, data structures or the like. It should beremembered, however, that all of these and similar terms are to beassociated with the appropriate physical quantities and are merelyconvenient labels applied to these quantities.

Further, the manipulations performed are often referred to in terms suchas identifying, fitting or comparing. In any of the operations describedherein that form part of the present invention these operations can bemachine operations. Useful machines for performing the operations ofembodiments of the present invention include general purpose digitalcomputers or other similar devices. In all cases, there should be bornein mind the distinction between the method of operations in operating acomputer and the method of computation itself. Embodiments of thepresent invention relate to method steps for operating a computer inprocessing electrical or other physical signals to generate otherdesired physical signals.

In addition, embodiments of the present invention further relate tocomputer readable media that include program instructions for performingvarious computer-implemented operations. Examples of computer-readablemedia include, but are not limited to, magnetic media such as harddisks, floppy disks, and magnetic tape; optical media such as CD-ROMdisks; magneto-optical media such as floptical disks; and hardwaredevices that are specially configured to store and perform programinstructions, such as read-only memory devices (ROM) and random accessmemory (RAM). Examples of program instructions include both machinecode, such as produced by a compiler, and files containing higher levelcode that may be executed by the computer using an interpreter.

The many features and advantages of the present invention are apparentfrom the written description, and thus, the appended claims are intendedto cover all such features and advantages of the invention. Further, thepresent invention is not limited to the exact construction and operationas illustrated and described. Therefore, the described embodimentsshould be taken as illustrative and not restrictive, and the inventionshould not be limited to the details given herein but should be definedby the following claims and their full scope of equivalents, whetherforeseeable or unforeseeable now or in the future.

1. A method comprising: receiving a data signal using a DSL (DigitalSubscriber Line); receiving a reference signal, the reference signalcorresponding, in part, to noise on the data signal; classifying thereference signal wherein classifying the reference signal comprisesestimating statistical properties of the reference signal and comparingthe statistical properties to a set of known properties; and applying anoise cancellation signal to the data signal based on theclassification.
 2. The method of claim 1, wherein receiving a datasignal comprises receiving the data signal on a telephone line within abinder and wherein receiving a reference signal comprises receiving asignal on a second telephone line that is within the same binder as thefirst telephone line.
 3. The method of claim 2, wherein the secondtelephone line carries analog voice and wherein receiving the referencesignal comprises filtering out the analog voice.
 4. The method of claim2, wherein the second telephone line carries DSL data using multipletones and wherein receiving the reference signal comprises receiving thereference signal on tones that are not used to carry DSL data. 5.(canceled)
 6. The method of claim 1, further comprising measuring thequality of the received data, for example by comparing the error rate ofthe data signal to a threshold, and if the quality is low, then notapplying the noise cancellation to the data signal.
 7. (canceled)
 8. Themethod of claim 1, wherein applying a noise cancellation signalcomprises selecting an entry in a classification table based on theestimated statistical properties and applying a correspondingcoefficient from the classification table.
 9. The method of claim 8,wherein applying the corresponding coefficient comprises applying thecoefficient to the reference signal to obtain the noise cancellationsignal and wherein applying the noise cancellation signal comprisessubtracting the noise cancellation signal from the data signal.
 10. Themethod of claim 1, wherein applying a noise cancellation signalcomprises selecting a coefficient from a plurality of candidatecoefficients and producing a noise cancellation signal using thecoefficient.
 11. The method of claim 10, further comprising determiningan error value for the data signal after applying the noise cancellationsignal and updating the corresponding coefficient by using thedetermined error value and applying it, for example, to a least meanssquare estimation.
 12. The method of claim 10, wherein the correspondingcoefficient is determined based on the classification of the referencesignal used in the noise cancellation signal.
 13. The method of claim 1,wherein applying the noise cancellation signal comprises applying eithera time domain or frequency domain noise cancellation signal to a datasignal that is in the same time or frequency domain, respectively.
 14. Amachine-readable medium storing thereon instructions that when executedby the machine cause the machine to perform the operations in claim 1.15. An apparatus comprising: a data receive chain to receive a datasignal; a reference signal receive chain to receive a noise signal; anoise classification module to characterize the noise signal; and anoise filter to apply a noise cancellation signal to the data signalbased on the characterization of the noise signal.
 16. The apparatus ofclaim 15, further comprising: a selector coupled to the noiseclassification module to select a subtraction coefficient based on thecharacterization of the noise signal; a multiplier to combine thecoefficient with the noise signal; and a subtractor to apply thecombined coefficient and noise signal to the data signal.